NIDA research monograph最新文献

Drug use among different populations such as household members, students, and arrestees vary substantially and the accuracy of their self-reports may be questionable. The accuracy of prevalence estimates based on self-report data can be monitored by chemical drug testing of biological specimens such as urine, saliva, sweat, and hair. Each biological specimen is unique and offers a somewhat different pattern of information regarding drug use over time. Also, each specimen has unique strengths and weaknesses regarding the type of information obtained from drug testing. The performance characteristics of the assay methodology may also be important. The validation of self-report data by drug testing must be performed with careful consideration of the limitations imposed by the testing methodology and the biological specimen.

Hair testing is only used by the Federal Bureau of Investigation (FBI) when other information exists that indicates drug use and can remove a person from suspicion or associate them with criminal activity. The detection of cocaine in hair has been the FBI's first priority in hair testing for drugs of abuse because of its prevalence. Several cases when hair testing was used are reported in this chapter. Further, analysis of over 100 samples was performed on hair obtained from a medical examiner's random autopsy collection. Sixty-five percent of the samples tested positive for cocaine or opiates. The results of hair testing for drugs of abuse were found to be consistent with autopsy toxicology reports. The analysis of hair washes and nails from the autopsy samples suggests external contamination of hair with drugs is not widespread.

A summary of the results of a series of studies of nonresponse and measurement error in the National Household Survey on Drug Abuse (NHSDA) is given in this chapter. Two studies not previously reported, the Skip Pattern Experiment and the Census Match Study, are the primary focus of the chapter. The Skip Pattern Experiment involved a test of a modified NHSDA questionnaire that made extensive use of skip patterns in drug use questions. Compared to the standard NHSDA method, which avoids skip patterns, the modified questionnaire tended to produce lower rates of reported drug use. The Census Match Study involved linking 1990 NHSDA nonrespondent cases with data from the 1990 Decennial Census. Household and individual data for NHSDA nonrespondents were obtained from the Census and used to characterize NHSDA nonresponse patterns in detail. A multilevel logistic model of response propensity identified the important predictors of nonresponse, including characteristics of the sampled person, the selected household, the neighborhood, and the interviewer.

This chapter reviews the literature on factors related to quality of self-report data on drug use and discusses two series of empirical studies investigating the quality of those data. One set of analyses examined the quality of the longitudinal retrospective self-report from narcotics addicts, including validity of recent narcotics use, reliability of various measures, stability of relationships among these measures, and pattern reliability among latent constructs. Results contribute strongly to confidence in the validity of the relationships among these data derived from addicts' self-report. The second set of analyses focused on validity of self-reported drug use among high-risk groups, including samples from sexually transmitted disease (STD) clinics, hospital emergency rooms (ERs), and jails. Results suggest that the accuracy of self-report of recent drug use varies by the sample sources, drug types, and subject characteristics. Targeting these high-risk groups may improve prevalence estimation. The chapter concludes that empirical validation of self-report is always necessary to enhance the utility of collected self-report data and provide means of controlling for potential biases.